4.2k citations · 4.2k across the 6 of their papers we have counts for
6 papers
PR3DICTR: A modular AI framework for medical 3D image-based detection and outcome prediction
Daniel C. MacRae, Luuk van der Hoek, Robert van der Wal +5
Three-dimensional medical image data and computer-aided decision making, particularly using deep learning, are becoming increasingly important in the medical field. To aid in these…
DASS Good: Explainable Data Mining of Spatial Cohort Data
Andrew Wentzel, Carla Floricel, Guadalupe Canahuate +5
Developing applicable clinical machine learning models is a difficult task when the data includes spatial information, for example, radiation dose distributions across adjacent org…
Slice-by-slice deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for spatial uncertainty on FDG PET and CT images
Alessia De Biase, Nanna Maria Sijtsema, Lisanne van Dijk +2
Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oropharyngeal cancer patients (OPC),…
THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy
Carla Floricel, Nafiul Nipu, Mikayla Biggs +6
Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resoluti…
Explainable Spatial Clustering: Leveraging Spatial Data in Radiation Oncology
Andrew Wentzel, Guadalupe Canahuate, Lisanne van Dijk +3
Advances in data collection in radiation therapy have led to an abundance of opportunities for applying data mining and machine learning techniques to promote new data-driven insig…
Image biomarker standardisation initiative
Alex Zwanenburg, Stefan Leger, Martin Vallières +1
The image biomarker standardisation initiative (IBSI) is an independent international collaboration which works towards standardising the extraction of image biomarkers from acquir…